Top Remote Data & Analytics Jobs in Dallas, TX

As a Pricing and Revenue Planner, you will manage pricing analytics, forecasting, synthesizing data into actionable insights, and collaborating with various teams to drive revenue improvements and profitability analysis.

Lead analytics for branch network optimization, new branch and ATM strategy by integrating internal and external data, producing actionable insights, presenting to senior leaders, and partnering cross-functionally to champion analytics best practices.

Lead product analytics for a B2B SaaS product: define metrics and measurement frameworks, analyze user behavior and product performance, build self-service dashboards, partner cross-functionally to link usage to business outcomes, and translate data into strategic recommendations for product roadmap and GTM decisions.

The Principal Data Scientist will lead data analysis projects, collaborate with product management, assess business impacts, ensure data governance, and mentor junior analysts. Must leverage statistical techniques and machine learning to drive product strategy and business outcomes.

The Senior Analyst in AML KYC will conduct detailed customer onboarding, monitor client relationships for compliance, and update KYC records while utilizing AI tools for efficiency.

Own and architect large-scale data pipelines, orchestration, and integrations. Drive IaC strategy (Terraform), third-party API and AI/LLM tool integrations, build export pipelines and internal tooling, mentor engineers, and align cross-team technical strategy for reliable, scalable data infrastructure.

Lead design and execution of Toast's enterprise data governance: define strategy, build governance frameworks, policies, business glossary, Data Governance Council, ensure compliance (GDPR/CCPA/SOC2/PCI-DSS), run maturity assessments, enable data literacy, and grow the governance team to drive adoption across domains.

The Senior Consumer Insights Analyst leads consumer insights within cross-functional teams by managing research processes, synthesizing data, and delivering actionable findings to influence product development and strategy.

Own implementation, maintenance, and optimization of client eligibility and claims data feeds. Analyze feed performance, troubleshoot discrepancies, produce error reports, test integrations with external partners, and improve internal tools, documentation, and processes to increase automation and reliability.

As the first in-house Data Engineer, you will own the data infrastructure, build and maintain data pipelines, and collaborate with teams to ensure quality data access and insights.